Integration of data from a variety of data sources is desirable in many enterprises. At present, attention has been focused on straightforward data querying and mapping in a distributed environment of heterogeneous data sources, involving data base management systems, knowledge bases, flat file systems, forms and spreadsheet applications, and the like. Such data querying typically allows users to specify search criteria using a query language such as structured query language (SQL), while data mapping is used to translate the queries and results between the heterogeneous back-end systems and the centralized integration platform. Although large-scale integration solutions are currently being built to offer efficient data retrieval, none support an infrastructure for complex relationship management of the data. Currently, specifications for data integration typically involve only explicit data mapping from multiple data sources. For example, U.S. Pat. No. 6,633,889 to Dessloch et al. teaches the mapping of persistent data objects residing in multiple data sources into a single, reusable software component accessible to an object-oriented programming language application performed by a computer, for multi-data base access to data that may be physically distributed and stored in disparate database management systems. A single virtual data object can be created based on registered data objects, and the virtual data object may be wrapped as a reusable software component.
Prior art solutions typically do not promote the use and identification of implicit information, i.e., complex relationship definition, on top of traditional explicit mapping. Further, in prior art systems, the user must traditionally issue multiple queries to piece together a final answer, for example, to develop a management chain. The user typically must have an overall view of the system's schema and structure in advance in order even to formulate appropriate queries. Finally, prior art systems are typically limited to the retrieval of explicit data and do not allow retrieval and maintenance of logical implications between the explicit pieces of data through generalized data structures.
In view of the foregoing, it is desirable to provide a system and method for managing complex relationships over distributed heterogeneous data sources. The system and method should promote use and identification of implicit information, that is, complex relationship definition, in addition to traditional explicit mapping, and should provide the user with the flexibility of defining any sort of desired relationship in a conceptually intuitive and visually explicit manner using, for example, extensible markup language (XML) scripts. It would also be desirable if the system and method permitted easy navigation by the user without requiring complex query formulation. Yet further, it would be desirable if the system and method allowed users to retrieve additional “implicit” data by treating the navigation structure and assembly itself as being a complex form of data.